6 June 2016

Why? Presenting research results

Nature, October 2014

Why? Teaching

Least squares estimation

Linear regression model

\[ y_i = \alpha + \beta x_i + \epsilon \]

Estimates for the intercept and slope can be found by minimizing the squared residuals.

\[ \arg\min_{\alpha, \beta} \sum_i \left(y_i - (\alpha + \beta x_i) \right)^2 \]





Why? Teaching

Why? Teaching

Why? Teaching

Why? Teaching

Slidify

library(shiny)
runGitHub('ekstroem/ShinyLeastSquares')

The "role" of graphics is changing and expanding

Background

Toby

  • Dept. XXX, XXX
  • R packages: animint
  • Some other nice info.
  • Change pic?




Claus

  • Dept. Biostatistics, UCPH
  • R packages: MESS, MethComp, SuperRanker, …
  • R book: The R Primer
  • Happy/frustrated interactive graphics enthusiast

Outline for the tutorial

Topic Time
Introduction 15 minutes
Highlevel interactive graphics (javascript libraries) 35 minutes
Interactive graphics (shiny, ggplotly) 35 minutes
Break
Multi layer/-panel graphics 30 minutes
Animated graphics 30 minutes
Putting it all together 30 minutes

Tutorial goals:

  1. Explain and emphasize the role that interactive graphics have in reporting, scientific journals, and in teaching.
  2. Give overview of existing R packages for interactive graphics.
  3. Explain the strengths and weaknesses of the existing R packages, to highlight directions for future work.

Necessary stuff

Necesary packages etc XXX To be filled out at the end

Rstudio

See also: Toby's link

devtools::install_github("ramnathv/rCharts")

Concepts

Tobys slides terms / discussion

  • multi-layer, multi-panel, multi-plot
  • animation, direct manipulation (clicking, hovering), indirect manipulation (buttons, menus)
  • zoom, highlight, show/hide (data, labels, tooltips)

An example of 1

An example of 2

An example of 3

The role of the graphics/viewer

Interactive graphics architechture

  • Distribution and viewing
  • Dedicated server vs. local server

Javascript-based libraries (htmlwidgets)

R and Javascript architecture

D3.js doesn’t ship with any pre-built charts out of the box. However, go to website to get an overview of the possibilities.

  • ChartJS
  • Chartist.js
  • [n3]
  • plotly

Highlevel interactive graphics

Numerous possibilities in R packages

  • rCharts (oldish - mix of libraries)
  • highcharter (standard plot types, mature library)
  • dygraphs (mostly time series. well documented. Rich features)
  • metricsgraphics (also time series)
  • leaflet (maps)
  • plotly (general plots - like ggplot)
  • htmlwidgets Javascript framework (many are part of this). Super important!





  • No standard interface
  • Not easily extendable from R
  • Pick a library and learn it!

rCharts interfaces

polychart (from rCharts)

plot/lattice-like function.

library(rCharts)
library(MESS)
data(happiness)
mydf <- happiness
mydf$size <- sqrt(mydf$population)/8
r1 <- rPlot(x = "tax", 
            y = "happy", 
            data = mydf, 
            type = "point", 
            color = "continent", 
            size = "size")
r1

Type: bar, layers, …

polychart (from rCharts)

plot/lattice-like function. Add layers and guides to plot ..

mydf2 <- data.frame(tax=c(1, 50), 
                happy=c(4.93, 7.09))

r1$layer(x = "tax", 
         y = "happy", 
         data = mydf2, 
         type = "line",
         size=list(const=4))

r1$guides(y = list(title="New label", 
                   min=0, max=12))

r1
  • layer \(\approx\) points/lines
  • guides \(\approx\) axis
  • addParams \(\approx\) title, plot size

polychart - tooltips

r3 <- rPlot(x = "tax", y = "happy", 
      data = mydf, type = "point", 
      color = "continent", 
      size = "size", 
      tooltip="#!function(item){ 
return ('Country: ' +item.country+ 
        '&#013; Tax: ' +item.tax+ 
        '% Happiness: ' +item.happy+
        '<br> Pop: ' +item.population+ 
        ' mio.') }!#")

Passing javascript is non-trivial.

Highcharts

HighCharter

highcharter

Mature charts, stocks (time series), maps. Good API.

  • Start with empty chart and add components.
  • (Mostly) no default arguments
library(highcharter)
hc <- highchart() %>% 
  hc_chart(type = "column") %>% 
  hc_title(text = "Denmark") %>% 
  hc_xAxis(categories = 2011:2016) %>% 
  hc_add_series(data = c(3806,  6184,  
                         7557, 14792, 
                         21315, 3016),
          name = "Asylum seekers") %>% 
  hc_add_serie(name = "Syria", 
               data = c(429, 822, 
                      1710, 7087, 
                       8608, 777),
               type = "spline")
hc





Highcharter - adding data

Data are added using one of the following functions

Name Function
hc_add_series Add single series (named: data, name)
hc_add_series_list Add list named series
hc_add_series_df Add data.frame. Name variables accordingly
hc_add_series_ts Add ts object. Extra argument: name
hc_add_series_scatter Crate scatter from two vectors. Extra arguments (size, color, label)
hc_add_series_boxplot Add boxplots
hc_add_series_map Add geojson map

Highcharter function overview

Function Example
Title hc_title(text = "Temperature")
Subtitle hc_subtitle(text = "Somewhere warm")
Axis hc_xAxis(categories = month)
hc_yAxis(title = list(text = "Temperature"), labels = list(format = "{value} C"))
Theme hc_add_theme(hc_theme_sandsignika())
Zoom hc_chart(zoomType = "xy")
Tooltip hc_tooltip(useHTML = TRUE, headerFormat="<table>",
pointFormat = "<tr><th>x-val</th><td>{point.x}</td></tr>"
footerFormat = "</table>")
Legend hc_legend(enabled=FALSE)
Credits hc_credits(enabled = TRUE, text = "Source: Wikipedia", href = "https://wikipedia.com", style = list(fontSize = "12px"))

Highcharter - adding information

happiness$size <- sqrt(happiness$population)/8

happy2 <- highchart() %>% 
  hc_title(text = "Taxes and happiness") %>% 
  hc_subtitle(text = "Source: Wikipedia") %>% 
  hc_xAxis(title = list(text = "Taxation (%)")) %>% 
  hc_yAxis(title = list(text = "Happiness")) %>% 
  hc_chart(zoomType = "xy") %>% 
  hc_add_serie_scatter(happiness$tax, happiness$happy,
                       happiness$size, happiness$continent,
                       happiness$country,
                       dataLabels = list(
                         enabled = TRUE,
                         format = "{point.label}"
                       ),
                       extrainfo = sprintf("Mostly %s", happiness$religion)
                       ) %>%
  hc_tooltip(useHTML = TRUE,
             headerFormat = "<table>",
             pointFormat = paste("<tr><th colspan=\"1\"><b>{point.label}</b></th></tr>",
                                 "<tr><th>Weight</th><td>{point.x} lb/1000</td></tr>",
                                 "<tr><th>MPG</th><td>{point.y} mpg</td></tr>",
                                 "<tr><th>Drat</th><td>{point.z} </td></tr>",
                                 "<tr><th>HP</th><td>{point.valuecolor} hp</td></tr>",
                                 "<tr><th>HP</th><td>{point.extrainfo} hp</td></tr>"),

             footerFormat = "</table>")
happy2

Highcharter - adding information

Highcharter - adding information

More on functions?

dygraphs

dygraphs

Same build-up as highcharter

library(dygraphs)
head(nhtemp)
dygraph(nhtemp, main = "New Haven Temperatures") %>% 
  dyRangeSelector(dateWindow = c("1920-01-01", "1960-01-01"))





dygraphs 2

dygraphs functions

| Function | Example | |——–+———-| | Title | hc_title(text = "Temperature") | | Subtitle | hc_subtitle(text = "Somewhere warm") | | Axis | hc_xAxis(categories = month) | | | hc_yAxis(title = list(text = "Temperature"), labels = list(format = "{value}? C")) | | Theme | hc_add_theme(hc_theme_sandsignika()) | | Zoom | hc_chart(zoomType = "xy") | | Tooltip | hc_tooltip(useHTML = TRUE, headerFormat=" ", | | | pointFormat = " " | | | footerFormat = "
x-val {point.x}

") | | Legend | hc_legend(enabled=FALSE) | | Credits | hc_credits(enabled = TRUE, text = "Source: Wikipedia", href = "https://wikipedia.com", style = list(fontSize = "12px")) |

metricsgraphics

Should be the same as before (happyness)

Metricgraphics

Metricgraphics

library(RColorBrewer)

tmp <- data.frame(year=seq(1790, 1970, 10), uspop=as.numeric(uspop))

tmp %>%
  mjs_plot(x=year, y=uspop) %>%
  mjs_point() %>%
  mjs_add_marker(1850, "Something Wonderful") %>%
  mjs_add_baseline(150, "Something Awful")

Metricgraphics

Metricgraphics function overview

| Function | Example | |——–+———-| | Title | hc_title(text = "Temperature") | | Subtitle | hc_subtitle(text = "Somewhere warm") | | Axis | hc_xAxis(categories = month) | | | hc_yAxis(title = list(text = "Temperature"), labels = list(format = "{value}? C")) | | Theme | hc_add_theme(hc_theme_sandsignika()) | | Zoom | hc_chart(zoomType = "xy") | | Tooltip | hc_tooltip(useHTML = TRUE, headerFormat=" ", | | | pointFormat = " " | | | footerFormat = "
x-val {point.x}

") | | Legend | hc_legend(enabled=FALSE) | | Credits | hc_credits(enabled = TRUE, text = "Source: Wikipedia", href = "https://wikipedia.com", style = list(fontSize = "12px")) |

leaflet

leaflet

library(leaflet)
library(MESS)


data(earthquakes)
m <- leaflet() %>%
  addTiles() %>%  # Add default OpenStreetMap map tiles
  addMarkers(lng=earthquakes$longitude[earthquakes$mag>6],          lat=earthquakes$latitude[earthquakes$mag>6], popup="Mag 6+")
m

leaflet

leaflet function overview

Exercise

rMaps - choropleths - out?

    <div class='container'>
      <input id='slider' type='range' min=1960 max=2010 ng-model='year' width=200>
      <span ng-bind='year'></span>
      <div id='chart7bc34e2b40bd' class='rChart datamaps'></div>          
    </div>
    <script>
      function rChartsCtrl($scope){
        $scope.year = 1960;
        $scope.$watch('year', function(newYear){
          mapchart7bc34e2b40bd.updateChoropleth(chartParams.newData[newYear]);
        })
      }
   </script>

Publishing interactive graphics

Note: html/js output. Need javascript machinery to run (ie., html with js code embedded or online link).

library(htmlwidgets)
saveWidget(widget, file, selfcontained = TRUE, background="white")

Including in R markdown

iframe

## <script type='text/javascript' src=/Users/cld189/Library/R/3.3/library/rCharts/libraries/polycharts/js/polychart2.standalone.js></script> 
##  <style>
##   .rChart {
##     display: block;
##     margin-left: auto; 
##     margin-right: auto;
##     width: 400px;
##     height: 500px;
##   }  
##   </style>
## <div id = 'chart7bc324848bb1' class = 'rChart polycharts'></div>
## <script type='text/javascript'>
##     var chartParams = {
##  "dom": "chart7bc324848bb1",
## "width":    400,
## "height":    500,
## "layers": [
##  {
##  "x": "tax",
## "y": "happy",
## "data": {
##  "country": [ "Andorra", "United Arab Emirate", "Afghanistan", "Albania", "Armenia", "Angola", "Argentina", "Austria", "Australia", "Azerbaijan", "Bosnia Herzegovina", "Bangladesh", "Belgium", "Burkina Faso", "Bulgaria", "Burundi", "Benin", "Bolivia", "Brazil", "Botswana", "Belarus", "Belize", "Canada", "Dem. Rep. of Congo", "Central African Rep", "Switzerland", "Ivory Coast", "Chile", "Cameroon", "China", "Colombia", "Costa Rica", "Cyprus", "Czech Republic", "Germany", "Djibouti", "Denmark", "Dominican Republic", "Algeria", "Ecuador", "Estonia", "Egypt", "Spain", "Ethiopia", "Finland", "France", "United Kingdom", "Georgia", "Ghana", "Guinea", "Greece", "Guatemala", "Guyana", "Hong Kong", "Honduras", "Croatia", "Haiti", "Hungary", "Indonesia", "Ireland", "Israel", "India", "Iraq", "Iran", "Iceland", "Italy", "Jamaica", "Jordan", "Japan", "Kenya", "Kyrgyzstan", "Cambodia", "Kosovo", "South Korea", "Kuwait", "Kazakhstan", "Laos", "Lebanon", "Sri Lanka", "Liberia", "Lithuania", "Luxembourg", "Latvia", "Morocco", "Moldova", "Montenegro", "Madagascar", "Macedonia", "Mali", "Mongolia", "Mauritania", "Malta", "Malawi", "Mexico", "Malaysia", "Mozambique", "Namibia", "Niger", "Nigeria", "Nicaragua", "Netherlands", "Norway", "Nepal", "New Zealand", "Panama", "Peru", "Philippines", "Pakistan", "Poland", "Palestina", "Portugal", "Paraguay", "Qatar", "Romania", "Serbia", "Russia", "Rwanda", "Saudi Arabia", "Sudan", "Sweden", "Singapore", "Slovenia", "Slovakia", "Sierra Leone", "Senegal", "El Salvador", "Syria", "Chad", "Togo", "Thailand", "Tajikistan", "Turkmenistan", "Tunisia", "Turkey", "Trinidad and Tobago", "Taiwan", "Tanzania", "Ukraine", "Uganda", "United States", "Uruguay", "Uzbekistan", "Venezuela", "Vietnam", "Yemen", "South Africa", "Zambia", "Zimbabwe" ],
## "happy": [    6.8,    7.3,    4.1,    4.6,      5,    4.3,    7.3,    7.6,    7.7,    5.3,    5.6,    5.3,    7.3,    4.4,    4.4,    2.9,      3,    6.5,    7.5,    4.7,    5.2,    6.6,    7.8,    4.4,    4.6,      8,    4.4,    6.6,    3.9,    6.3,    7.7,    8.5,    7.1,    6.5,    7.1,    5.7,    8.3,    7.6,    5.4,    6.4,      6,    5.7,    7.2,    4.2,    7.9,    6.6,    7.1,    4.3,    5.2,    4.5,    6.4,    7.2,    6.5,    6.6,      7,      6,    3.9,    5.5,    6.3,    7.6,      7,    5.5,    4.7,    5.9,    8.2,    6.7,    6.7,    5.9,    6.5,    3.7,    5.5,    4.9,    5.4,      6,    6.6,    6.1,    6.2,    4.7,    5.1,    4.3,    5.5,    7.7,    5.4,    5.4,    4.9,    5.2,    3.7,    4.7,    4.7,    5.7,    4.9,    7.1,    6.2,    7.9,    6.5,    3.8,    5.2,    3.8,    5.7,    7.1,    7.6,    7.9,    5.3,    7.5,    7.8,    6.2,    5.9,      5,    6.4,    4.9,    5.7,    6.9,    6.8,    5.7,    5.4,    5.5,    4.3,    6.5,      5,    7.8,    6.9,    6.9,    5.9,    3.5,    4.5,    6.7,    5.9,    5.4,    2.6,    6.6,    5.1,    7.2,    5.9,    5.6,      7,    6.2,    2.8,      5,    4.8,    7.4,    6.8,      6,    7.5,    6.1,    4.8,    5.8,      5,      3 ],
## "tax": [ null,    1.4,    6.4,   22.9,   14.1,    5.7,   37.2,   43.4,   30.8,   17.8,   41.2,    8.5,   46.8,   11.5,   34.4,   17.4,   15.4,     27,   34.4,   35.2,   24.2,   21.6,   35.2,    5.9,    7.7,   29.4,   15.3,   18.6,   18.2,     17,     23,     14,   39.2,   36.3,   40.6,     20,     49,     15,    7.7,   13.2,   32.3,   15.8,   37.3,   11.6,   43.6,   44.6,     39,   21.7,   20.8,    8.2,   33.5,   11.9,   31.9,     13,   15.6,   26.6,    9.4,   39.1,     12,   30.8,   36.8,   17.7, null,    6.1,   40.4,   42.6,   27.2,   21.1,   28.3,   18.4,   21.4,      8, null,   26.8,    1.5,   26.8,   10.8,   14.4,   15.3,   13.2,   20.9,   36.5,   30.4,   22.3,   33.8,     28,   10.7,   29.3,   15.3,   33.8,   15.4,   35.2,   20.7,   29.7,   15.5,   13.4,   28.8,     11,    6.1,   17.8,   39.8,   43.6,   10.9,   34.5,   10.6,   15.1,   14.4,   10.2,   33.8, null,     37,     12,    2.2,   28.1,   34.1,   36.9,   14.1,    5.3,    6.3,   47.9,   14.2,   39.3,   29.5,   10.5,   19.2,   13.3,   10.7,    4.2,   15.5,     17,   16.5,   20.2,   14.9,   32.5,     28,   12.4,     12,   38.1,   12.6,   26.9,   23.1,     21,     25,   13.8,    7.1,   26.9,   16.1,   49.3 ],
## "religion": [ "Christian", "Muslim", "Muslim", "Muslim", "Christian", "Christian", "Christian", "Christian", "Christian", "Muslim", "Christian", "Muslim", "Christian", "Muslim", "Christian", "Christian", "Christian", "Christian", "Christian", "Christian", "Christian", "Christian", "Christian", "Christian", "Christian", "Christian", "None", "Christian", "Christian", "None", "Christian", "Christian", "Christian", "None", "Christian", "Muslim", "Christian", "Christian", "Muslim", "Christian", "None", "Muslim", "Christian", "Christian", "Christian", "None", "Christian", "Christian", "Christian", "Muslim", "Christian", "Christian", "Christian", "Buddhist", "Christian", "Christian", "Christian", "Christian", "Muslim", "Christian", "Other", "Hindu", "Muslim", "Muslim", "Christian", "Christian", "Christian", "Muslim", "Buddhist", "Christian", "Muslim", "Buddhist", null, "None", "Muslim", "Muslim", "Buddhist", "Muslim", "Buddhist", "Christian", "Christian", "Christian", "Christian", "Muslim", "Christian", "Christian", "Other", "Christian", "Muslim", "None", "Muslim", "Christian", "Christian", "Christian", "Muslim", "Christian", "Christian", "Muslim", "Muslim", "Christian", "None", "Christian", "Hindu", "Christian", "Christian", "Christian", "Christian", "Muslim", "Christian", "Muslim", "Christian", "Muslim", "Muslim", "Christian", "Christian", "Christian", "Christian", "Muslim", "Muslim", "Christian", "Buddhist", "Christian", "Christian", "Muslim", "Muslim", "Christian", "Muslim", "Muslim", "Other", "Buddhist", "Muslim", "Muslim", "Muslim", "Muslim", "Christian", "Buddhist", "Christian", "Christian", "Christian", "Christian", "Christian", "Muslim", "Christian", "Buddhist", "Muslim", "Christian", "Christian", "Christian" ],
## "continent": [ "EU", "AS", "AS", "EU", "EU", "AF", "SA", "EU", "OC", "EU", "EU", "AS", "EU", "AF", "EU", "AF", "AF", "SA", "SA", "AF", "EU", "NA", "NA", "AF", "AF", "EU", "AF", "SA", "AF", "AS", "SA", "NA", "EU", "EU", "EU", "AF", "EU", "NA", "AF", "SA", "EU", "AF", "EU", "AF", "EU", "EU", "EU", "EU", "AF", "AF", "EU", "NA", "SA", "AS", "NA", "EU", "NA", "EU", "AS", "EU", "AS", "AS", "AS", "AS", "EU", "EU", "NA", "AS", "AS", "AF", "AS", "AS", "EU", "AS", "AS", "AS", "AS", "AS", "AS", "AS", "EU", "EU", "EU", "AF", "EU", "EU", "AF", "EU", "AF", "AS", "AF", "EU", "AF", "NA", "AS", "AF", "AF", "AF", "AF", "NA", "EU", "EU", "AS", "OC", "NA", "SA", "AS", "AS", "EU", "AS", "EU", "SA", "AS", "EU", "EU", "EU", "AF", "AS", "AF", "EU", "AS", "EU", "EU", "AF", "AF", "NA", "AS", "AF", "AF", "AS", "AS", "AS", "AF", "AS", "NA", "AS", "AF", "EU", "AF", "NA", "SA", "AS", "SA", "AS", "AS", "AF", "AF", "AF" ],
## "population": [  0.078,  8.264,   25.5,  2.831,  3.268, 20.609, 40.117,  8.452, 22.687,  9.235,  3.839, 152.52, 10.951,  15.73,  7.364,  8.749,  9.352, 10.426, 192.38,  2.038,  9.458,  0.312, 34.875, 69.575,  4.576,  7.952, 20.595, 17.402, 19.406, 1347.3, 46.631,  4.301,  0.838, 10.504, 81.859,  0.923,  5.584,  9.445,   37.1, 14.483,  1.294, 82.448, 46.185,  84.32,  5.413,  65.35, 62.262,  4.497, null, 10.481, 10.787, 14.713,  0.784,  7.103,  8.385,   4.29, 10.085,  9.962, 237.64,  4.588,  7.879, 1210.2,  33.33, 75.149,   0.32, 60.813,  2.705,  6.329, 127.53, 42.749,  5.477, 14.479, null,  48.58,  3.582, 16.734,  6.465,  4.292, 20.277,  4.245,  3.187,  0.511,   2.07, 32.628,  3.559,   0.62, 20.696, 2.0557, 16.319,  2.844,  3.378,  0.417, 15.883, 112.34, 28.334,   23.7,  2.364, 16.274, 166.63,  5.815, 16.736,  5.026,  26.62,  4.434,  3.405, 30.135, 92.337, 180.27, 38.501,  4.293, 10.561,  6.337,  1.699, 19.042,   7.12, 143.12, 10.718, 27.136, 30.894,  9.495,  5.183,  2.057,  5.445,  6.126, 12.855,  6.183, 21.684, 11.831,  6.191, 65.479,    7.8,   5.17, 10.673, 74.724,  1.317, 23.261, 43.188, 45.589, 32.939, 314.03,  3.251, 29.123,  27.15,  87.84, 24.527, 50.586, 13.046, 13.014 ],
## "size": [ 0.034911, 0.35934, 0.63122, 0.21032, 0.22597, 0.56746, 0.79172, 0.3634, 0.59539, 0.37986, 0.24492, 1.5437, 0.41365, 0.49576, 0.33921, 0.36973, 0.38226, 0.40362, 1.7337, 0.17845, 0.38442, 0.069821, 0.73819, 1.0426, 0.26739, 0.35249, 0.56727, 0.52145, 0.55065, 4.5883, 0.85359, 0.25924, 0.11443, 0.40512, 1.1309, 0.12009, 0.29538, 0.38416, 0.76137, 0.47571, 0.14219,  1.135, 0.84949, 1.1478, 0.29082, 1.0105, 0.98633, 0.26508, null, 0.40468, 0.41054, 0.47947, 0.11068, 0.33314, 0.36196, 0.2589, 0.39696, 0.39453,  1.927, 0.26775, 0.35087, 4.3485, 0.72165, 1.0836, 0.070711, 0.97478, 0.20559, 0.31447, 1.4116, 0.81728, 0.29254, 0.47564, null, 0.87124, 0.23658, 0.51134, 0.31783, 0.25896, 0.56287, 0.25754, 0.22315, 0.089355, 0.17984, 0.71401, 0.23582, 0.098425, 0.56866, 0.17922, 0.50496, 0.2108, 0.22974, 0.080719, 0.49817, 1.3249, 0.66537, 0.60853, 0.19219, 0.50426, 1.6136, 0.30143, 0.51137, 0.28023, 0.64493, 0.26321, 0.23066, 0.68619, 1.2012, 1.6783, 0.77561, 0.25899, 0.40622, 0.31467, 0.16293, 0.54546, 0.33354, 1.4954, 0.40923, 0.65115, 0.69478, 0.38517, 0.28458, 0.17928, 0.29168, 0.30938, 0.44817, 0.31082, 0.58208, 0.42995, 0.31102, 1.0115, 0.34911, 0.28422, 0.40837, 1.0805, 0.14345, 0.60287, 0.82147,  0.844, 0.71741, 2.2151, 0.22538, 0.67457, 0.65132, 1.1715, 0.61906, 0.88905, 0.45149, 0.45094 ] 
## },
## "facet": null,
## "type": "point",
## "color": "continent",
## "size": "size" 
## } 
## ],
## "facet": [],
## "guides": [],
## "coord": [],
## "id": "chart7bc324848bb1" 
## }
##     _.each(chartParams.layers, function(el){
##         el.data = polyjs.data(el.data)
##     })
##     var graph_chart7bc324848bb1 = polyjs.chart(chartParams);
## </script>

plotly and ggplotly

Differences to other libraries … public

ggplotly - ggplot2

Exercise

ggiraph

Shiny

Shiny

Use standard R. Rather simple and beautiful. Simple input - no fancy transitions. Requires server

Example

library(shiny)
runGitHub('ekstroem/ShinySampleMean')

Quick introduction to Shiny

Shiny User Interface

Shiny server interface

Example

ui.R

server.R

Building the user interface

User interface functions

Example -> product

Building the server side

Server side functions

Example -> product

Finished product

ui.R

server.R

Running apps

Running apps from Github

Exercise